Fuzzy associative memories for instrument fault detection

A. Sharif Heger, Keith Holbert, A. Muneer Ishaque

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach.

Original languageEnglish (US)
Pages (from-to)739-756
Number of pages18
JournalAnnals of Nuclear Energy
Volume23
Issue number9
DOIs
StatePublished - Jun 1996

ASJC Scopus subject areas

  • Nuclear Energy and Engineering

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